Eigenspace method for text retrieval in historical document images

A new method for text retrieval that does not need segmentation is described. Segmenting the images in historical documents into individual characters is difficult. Therefore, the conventional OCR method, which uses segmentation, does not work well. Our method instead divides the text image into a sequence of small slits. The image region that corresponds to the query image region is retrieved by solving the matching problem of these sequences. Applying the eigenspace method to the slit images enables us to solve the matching problem efficiently. Moreover using dynamic time warping (DTW) further improves the results. Our method has higher accuracy than the simple template matching method, and it has far higher efficiency in computational cost.